Methods for Identifying Microbial Natural Product Compounds that Target Kinetoplastid RNA Structural Motifs by Homology and De Novo Modeled 18S rRNA
| Autor: | Edward K. Muge, Harrison Ndung'u Mwangi, Peter Waiganjo Wagacha, Albert Ndakala, Francis Mulaa |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Computer science natural products Genes Protozoan Protozoan Proteins Ligands 01 natural sciences Drug Discovery Protein Interaction Mapping Biology (General) Kinetoplastida Leishmaniasis Spectroscopy Drug discovery General Medicine Computer Science Applications Molecular Docking Simulation Chemistry 18S rRNA homology and de novo modeling Natural Products Chemistry QH301-705.5 In silico Computational biology Molecular Dynamics Simulation 010402 general chemistry Catalysis Article Inorganic Chemistry 03 medical and health sciences Trypanosomiasis RNA Ribosomal 18S Animals Humans Chagas Disease Homology modeling Physical and Theoretical Chemistry Molecular Biology QD1-999 Virtual screening Biological Products Organic Chemistry RNA Computational Biology molecular docking Ribosomal RNA virtual screening 0104 chemical sciences kinetoplastids 030104 developmental biology Docking (molecular) RNA Ribosomal |
| Zdroj: | International Journal of Molecular Sciences International Journal of Molecular Sciences, Vol 22, Iss 4493, p 4493 (2021) Volume 22 Issue 9 |
| ISSN: | 1422-0067 |
| Popis: | The development of novel anti-infectives against Kinetoplastids pathogens targeting proteins is a big problem occasioned by the antigenic variation in these parasites. This is also a global concern due to the zoonosis of these parasites, as they infect both humans and animals. Therefore, we need not only to create novel antibiotics, but also to speed up the development pipeline for these antibiotics. This may be achieved by using novel drug targets for Kinetoplastids drug discovery. In this study, we focused our attention on motifs of rRNA molecules that have been created using homology modeling. The RNA is the most ambiguous biopolymer in the kinetoplatid, which carries many different functions. For instance, tRNAs, rRNAs, and mRNAs are essential for gene expression both in the pro-and eukaryotes. However, all these types of RNAs have sequences with unique 3D structures that are specific for kinetoplastids only and can be used to shut down essential biochemical processes in kinetoplastids only. All these features make RNA very potent targets for antibacterial drug development. Here, we combine in silico methods combined with both computational biology and structure prediction tools to address our hypothesis. In this study, we outline a systematic approach for identifying kinetoplastid rRNA-ligand interactions and, more specifically, techniques that can be used to identify small molecules that target particular RNA. The high-resolution optimized model structures of these kineoplastids were generated using RNA 123, where all the stereochemical conflicts were solved and energies minimized to attain the best biological qualities. The high-resolution optimized model’s structures of these kinetoplastids were generated using RNA 123 where all the stereochemical conflicts were solved and energies minimized to attain the best biological qualities. These models were further analyzed to give their docking assessment reliability. Docking strategies, virtual screening, and fishing approaches successfully recognized novel and myriad macromolecular targets for the myxobacterial natural products with high binding affinities to exploit the unmet therapeutic needs. We demonstrate a sensible exploitation of virtual screening strategies to 18S rRNA using natural products interfaced with classical maximization of their efficacy in phamacognosy strategies that are well established. Integration of these virtual screening strategies in natural products chemistry and biochemistry research will spur the development of potential interventions to these tropical neglected diseases. |
| Databáze: | OpenAIRE |
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